1. Field
The following description relates to a computer-aided diagnostic technique, and to an apparatus and method for diagnosis that uses categorized diagnostic models.
2. Description of the Related Art
Computer-aided diagnosis (CAD) systems are diagnostic systems capable of reducing radiologists' workload by highlighting suspicious portions in a medical image based on the results of a quantitative analysis conducted by a computer so as to facilitate radiologists in making their final diagnoses.
CAD systems use various algorithms to make diagnoses of lesions. Such algorithms establish a diagnostic model through the learning of a large amount of data and classify newly input data based on the established diagnostic model. Accordingly, the performance of a CAD system in classifying the input data highly depends on the established diagnostic model. It is thus desirable to generate a diagnostic model by collecting and learning as much data as possible. However, creating an accurate diagnostic model is still difficult. In general, the more data is collected, the more precise the diagnosis is likely to be. However, this holds true only for the case of lesions that are common among the studied population from which the learning data was collected. Some cases of lesions may be less common among the population from which the learning data was collected, and certain set of data may present lesions differently. Thus, it may still be hard to detect lesions with unusual shapes or features based on the learning data, even if the size of the learning data is large.